Foodborne bacteria have persisted as a significant threat to public health and to the food and agriculture industry. Due to the widespread impact of these pathogens, there has been a push for the development of strategies that can rapidly detect foodborne bacteria on-site. Shiga toxin-producing E. coli strains (such as E. coli O157:H7, E. coli O121, and E. coli O26) from contaminated food have been a major concern. They carry genes stx1 and/or stx2 that produce two toxins, Shiga toxin 1 and Shiga toxin 2, which are virulent proteins. In this work, we demonstrate the development of a rapid test based on an isothermal recombinase polymerase amplification reaction for two Shiga toxin genes in a single reaction. Results of the amplification reaction are visualized simultaneously for both Shiga toxins on a single lateral flow paper strip. This strategy targets the DNA encoding Shiga toxin 1 and 2, allowing for broad detection of any Shiga toxin-producing bacterial species. From sample to answer, this method can achieve results in approximately 35 min with a detection limit of 10 CFU/mL. This strategy is sensitive and selective, detecting only Shiga toxin-producing bacteria. There was no interference observed from non-pathogenic or pathogenic non-Shiga toxin-producing bacteria. A detection limit of 10 CFU/mL for Shiga toxin-producing E. coli was also obtained in a food matrix. This strategy is advantageous as it allows for timely identification of Shiga toxin-related contamination for quick initial food contamination assessments.
more »
« less
A Low-Cost, 3D-Printed Biosensor for Rapid Detection of Escherichia coli
Detection of bacterial pathogens is significant in the fields of food safety, medicine, and public health, just to name a few. If bacterial pathogens are not properly identified and treated promptly, they can lead to morbidity and mortality, also possibly contribute to antimicrobial resistance. Current bacterial detection methodologies rely solely on laboratory-based techniques, which are limited by long turnaround detection times, expensive costs, and risks of inadequate accuracy; also, the work requires trained specialists. Here, we describe a cost-effective and portable 3D-printed electrochemical biosensor that facilitates rapid detection of certain Escherichia coli (E. coli) strains (DH5α, BL21, TOP10, and JM109) within 15 min using 500 μL of sample, and costs only USD 2.50 per test. The sensor displayed an excellent limit of detection (LOD) of 53 cfu, limit of quantification (LOQ) of 270 cfu, and showed cross-reactivity with strains BL21 and JM109 due to shared epitopes. This advantageous diagnostic device is a strong candidate for frequent testing at point of care; it also has application in various fields and industries where pathogen detection is of interest.
more »
« less
- PAR ID:
- 10339034
- Date Published:
- Journal Name:
- Sensors
- Volume:
- 22
- Issue:
- 6
- ISSN:
- 1424-8220
- Page Range / eLocation ID:
- 2382
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Parvinzadeh Gashti, Mazeyar (Ed.)The simple, accurate, and rapid detection of foodborne pathogens is essential for public health. Development of an immunomagnetic separation (IMS) multiplex touchdown PCR (IMS–multiplex TD–PCR) assay for simultaneous detection and distinguishing of C. jejuni and C. coli is reported herein. Polyclonal antibody (pAb) against multiepitope antigen (MEA) was conjugated to ferromagnetic nanoparticles (FMNs) to produce anti-MEA FMNs. Optimal anti-MEA FMNs loading yielded 26.7 μg of immunoglobulin G (IgG) molecules per mg of FMNs with an average size of 72 ± 9 nm, corresponding to an 83% rate of pAb conjugation. Anti-MEA FMNs (20 μg) for IMS captured culturable C. jejuni cells at 3.54 × 10 2 colony-forming unit (CFU)/mL in pure culture, while higher amounts (40 and 60 μg) reduced the recovery. The scanning electron microscope (SEM) analysis revealed the attachment of anti-MEA FMNs to target bacteria, forming aggregated cells and magnetic nanoparticles in ellipse-like shapes. The subsequent multiplex TD–PCR assay simultaneously detected and distinguished C. jejuni and C. coli at 104 CFU/mL in mixed culture and at 103 CFU/mL for each individual species. Furthermore, the limit of detection (LOD) of the IMS–multiplex TD–PCR assay was 104 CFU/g in spiked chicken breast samples. Specificity was 100% for both C. jejuni and C. coli as none of the amplicons were detected in control samples where Campylobacter was absent. This assay is able to detect and distinguish C. jejuni and C. coli simultaneously and is simple, accurate, and rapid with a time to result of 4 h without an enrichment step, making it a promising approach for rapid and culture-free detection of Campylobacter in chicken products.more » « less
-
Abstract Wastewater-based epidemiology (WBE) is a powerful tool for monitoring community disease occurrence, but current methods for bacterial detection suffer from limited scalability, the need fora prioriknowledge of the target organism, and the high degree of genetic similarity between different strains of the same species. Here, we show that surface-enhanced Raman spectroscopy (SERS) can be a scalable, label-free method for detection of bacteria in wastewater. We preferentially enhance Raman signal from bacteria in wastewater using positively-charged plasmonic gold nanorods (AuNRs) that electrostatically bind to the bacterial surface. Transmission cryoelectron microscopy (cryoEM) confirms that AuNRs bind selectively to bacteria in this wastewater matrix. We spike the bacterial speciesStaphylococcus epidermidis, Staphylococcus aureus, Serratia marcescens, andEscerichia coliand AuNRs into filter-sterilized wastewater, varying the AuNR concentration to achieve maximum signal across all pathogens. We then collect 540 spectra from each species, and train a machine learning (ML) model to identify bacterial species in wastewater. For bacterial concentrations of 109cells/mL, we achieve an accuracy exceeding 85%. We also demonstrate that this system is effective at environmentally-realistic bacterial concentrations, with a limit of bacterial detection of 104cells/mL. These results are a key first step toward a label-free, high-throughput platform for bacterial WBE.more » « less
-
null (Ed.)Urinary tract infection (UTI) is one of the most common infections, accounting for a substantial portion of outpatient hospital and clinic visits. Standard diagnosis of UTI by culture and sensitivity can take at least 48 h, and improper diagnosis can lead to an increase in antibiotic resistance following therapy. To address these shortcomings, rapid bioluminescence assays were developed and evaluated for the detection of UTI using intact, viable cells of Photobacterium mandapamensis USTCMS 1132 or previously lyophilized cells of Photobacterium leiognathi ATCC 33981™. Two platform technologies—tube bioluminescence extinction technology urine (TuBETUr) and cellphone-based UTI bioluminescence extinction technology (CUBET)—were developed and standardized using artificial urine to detect four commonly isolated UTI pathogens—namely, Escherichia coli, Proteus mirabilis, Staphylococcus aureus, and Candida albicans. Besides detection, these assays could also provide information regarding pathogen concentration/level, helping guide treatment decisions. These technologies were able to detect microbes associated with UTI at less than 105 CFU/mL, which is usually the lower cut-off limit for a positive UTI diagnosis. Among the 29 positive UTI samples yielding 105–106 CFU/mL pathogen concentrations, a total of 29 urine specimens were correctly detected by TuBETUr as UTI-positive based on an 1119 s detection window. Similarly, the rapid CUBET method was able to discriminate UTIs from normal samples with high confidence (p ≤ 0.0001), using single-pot conditions and cell phone-based monitoring. These technologies could potentially address the need for point-of-care UTI detection while reducing the possibility of antibiotic resistance associated with misdiagnosed cases of urinary tract infections, especially in low-resource environments.more » « less
-
Parkhill, Julian (Ed.)ABSTRACT RNA transcripts are potential therapeutic targets, yet bacterial transcripts have uncharacterized biodiversity. We developed an algorithm for transcript prediction called tp.py using it to predict transcripts (mRNA and other RNAs) inEscherichia coliK12 and E2348/69 strains (Bacteria:gamma-Proteobacteria),Listeria monocytogenesstrains Scott A and RO15 (Bacteria:Firmicute),Pseudomonas aeruginosastrains SG17M and NN2 strains (Bacteria:gamma-Proteobacteria), andHaloferax volcanii(Archaea:Halobacteria). From >5 millionE. coliK12 and >3 millionE. coliE2348/69 newly generated Oxford Nanopore Technologies direct RNA sequencing reads, 2,487 K12 mRNAs and 1,844 E2348/69 mRNAs were predicted, with the K12 mRNAs containing more than half of the predictedE. coliK12 proteins. While the number of predicted transcripts varied by strain based on the amount of sequence data used, across all strains examined, the predicted average size of the mRNAs was 1.6–1.7 kbp, while the median size of the 5′- and 3′-untranslated regions (UTRs) were 30–90 bp. Given the lack of bacterial and archaeal transcript annotation, most predictions were of novel transcripts, but we also predicted many previously characterized mRNAs and ncRNAs, including post-transcriptionally generated transcripts and small RNAs associated with pathogenesis in theE. coliE2348/69LEEpathogenicity islands. We predicted small transcripts in the 100–200 bp range as well as >10 kbp transcripts for all strains, with the longest transcript for two of the seven strains being thenuooperon transcript, and for another two strains it was a phage/prophage transcript. This quick, easy, and reproducible method will facilitate the presentation of transcripts, and UTR predictions alongside coding sequences and protein predictions in bacterial genome annotation as important resources for the research community.IMPORTANCEOur understanding of bacterial and archaeal genes and genomes is largely focused on proteins since there have only been limited efforts to describe bacterial/archaeal RNA diversity. This contrasts with studies on the human genome, where transcripts were sequenced prior to the release of the human genome over two decades ago. We developed software for the quick, easy, and reproducible prediction of bacterial and archaeal transcripts from Oxford Nanopore Technologies direct RNA sequencing data. These predictions are urgently needed for more accurate studies examining bacterial/archaeal gene regulation, including regulation of virulence factors, and for the development of novel RNA-based therapeutics and diagnostics to combat bacterial pathogens, like those with extreme antimicrobial resistance.more » « less
An official website of the United States government

